Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI.

What is The Role

We are looking for a Technical Lead to guide the technical direction of the Data Signals team and to extend that direction beyond the team. You will build and shape the capabilities and tools that simplify how security data is collected, processed, and experienced across different operational and analytical contexts—both when engineers build integrations and when teams analyze data to derive security insights. This role is about the end-to-end data experience: understanding developer and operational friction points across collection and data usage, and driving technical solutions that accelerate insights and improve developer productivity.

The Data Signals team owns tooling to support data telemetry pipelines, and data interpretation. That includes infrastructure and deployment tooling built on Terraform, telemetry pipelines running through BigQuery, and the AI-driven tools and evaluations used to interpret data and transform raw logs into actionable intelligence. As Technical Lead, you will set the technical strategy across these areas, break ambiguous problems into executable engineering initiatives, and drive end-to-end ownership of projects across data collection, telemetry, and AI-assisted data experiences.

This is fast-moving, often ambiguous work. We are looking for someone who is comfortable operating without a fixed spec, listens thoughtfully, and collaborates well across teams. You should drive toward outcomes while supporting your teammates, bring clear ideas on how data should be collected, structured, and presented, care deeply about the user and developer experience, and be equally comfortable working independently or alongside product teams and partners. You will be recognized as a technical authority beyond the team, using that standing to align data architecture, collection strategies, and standards across the Security, Ingest, and Analytics ecosystems.

Prior experience with the Elastic product suite isn't required, but it helps.

What you will be doing

Set the technical direction for the Data Signals team, owning the overarching architecture, data collection workflows, and automation strategy while using Gen AI to solve complex data experience problems at scale
Lead green-field initiatives that shape the future of multi-context data experiences, including multi-quarter, cross-team projects spanning integrations, and data presentation
Identify the highest-value problems, break them into well-scoped work that other engineers can execute, and take full ownership of the outcome
Make and document technical decisions, distinguishing one-way door decisions that need rigor from two-way door decisions that should move quickly
Work with the Engineering Manager and Product Management to define and influence the team's roadmap and to plan and prioritize delivery
Influence outside the team: align roadmaps, interfaces, and standards with the Security and Ingest teams and other engineering groups, resolve cross-team technical disagreements through discussion and compromise, and bring the needs of dependent teams back into the team's plans
Represent the team in the open, working with Elastic users and the broader open source community to shape direction and build trust, including presenting to broad technical and non-technical audiences
Set a collaborative tone for the team by fostering open communication, mutual respect, and thoughtful decision-making, and mentor engineers technically and in thinking about the whole product